R錯誤：維數不正確

Question

我有一些分類數據顯示植物家族，水果類型，果實顏色和種子散佈，其中響應變量（散佈）爲0代表否或1代表是。

test1.3 
      FAMILY FRUIT_TYPE COLOUR_RF Dispersal 
3 Erythroxylaceae   D   R   1 
4   Lamiaceae   D   G   1 
8  Clusiaceae   D   Y   1 
12  Clusiaceae   D   Y   1 
16  Myrtaceae   D   R   1 
19  Rubiaceae   D   R   0 
22 Anacardiaceae   D  Br   1 
25 Melastomataceae   D   R   1 
29   Moraceae   F   Y   1 
32   Moraceae   F  Br   1 
35   Fabaceae   C  Br   1 
37  Lauraceae   D  PG   1 
39  Sapindaceae   D  Br   1 
41  Myrtaceae   D   R   1 
43   Moraceae   D   G   1 
45  Clusiaceae   D   Y   1 
51   Moraceae   F   Y   1 
52  Lauraceae   D   R   0 
54  Rubiaceae   D   Y   0 
57 Euphorbiaceae   D  PY   0 
75 Dichapetalaceae   D   Y   1 
83   Moraceae   F   R   1 
86  Myrtaceae   D   Y   1 
91  Solanaceae   D   Y   1 
94  Myrsinaceae   D   Y   1 
98  Connaraceae   D   O   1 
101  Ochnaceae   C   R   1 
104  Proteaceae   D  Br   0 
107  Clusiaceae   D   R   1 
114  Clusiaceae   D   P   1 
116  Clusiaceae   D   P   1 
119  Smilacaceae   D   R   1 
124  Apocynaceae   D   Y   1 
129  Apocynaceae   D  Br   1 
138  Icacinaceae   D   Y   0 
141  Moraceae   D   Y   1 
144  Myrsinaceae   D   R   0 
147 Pittosporaceae   D   O   1 
150  Sapindaceae   C   O   1 
154  Fabaceae   C   Y   1 
158  Aphloiaceae   C   W   1 
169 Celastraceae   D   O   1 
176  Oleaceae   D   P   0 
179  Rubiaceae   D   Y   0 
182  Meliaceae   D   R   0 
186  Apocynaceae   C  PY   1 
188  Salicaceae   D   R   1 
192  Burseraceae   D  Br   0 
195   Araceae   D   Y   0 
198  Rubiaceae   D   P   1 
202  Rutaceae   D   O   1 
206 Torrecilliaceae   D  PY   0 
214  Arecaceae   D  PY   1 
220  Rutaceae   D  PY   0 
223  Rubiaceae   D  DR   0 
230  Rubiaceae   D   B   0 
237  Clusiaceae   D   Y   1 
244  Myrsinaceae   D   R   1 
247 Melastomataceae   D   R   0 
250 Aquifoliacea   D   R   1 
260  Marsaceae   D   W   1 
263  Vitaceae   D  DR   0 
266  Lamiaceae   D   B   0 
278 Hypericaceae   D   O   1 
281  Cannelaceae   D   Y   0 
283  Rubiaceae   D   R   1 
289  Sapotaceae   D  Br   1 
293  Lauraceae   D   R   0 
343  Sapindaceae   D   O   0 
344  Lauraceae   D   P   0 
362  Clusiaceae   D  Gr   1 
366 Anacardiaceae   D  Br   1 
370  Lauraceae   D   P   1 
374  Lauraceae   D   R   0 
399  Lauraceae   D   R   0 
405  Lauraceae   D   R   0 

我正在執行二項式GLM，並使用MuMIn軟件包'疏通'全局模型。

Global<-glm(Dispersal~FAMILY+COLOUR_RF+FRUIT_TYPE+COLOUR_RF*FRUIT_TYPE+COLOUR_RF*FAMILY, family=binomial(link="logit"), na.action="na.fail", data=test1.3) 

當我嘗試基於AICC重量繪製最顯著模型（正如我與其他迭代之前做過很多次），我得到警告錯誤：

library(MuMIn) 
    x<-dredge(Global) 

Fixed term is "(Intercept)" 
Warning messages: 
1: glm.fit: fitted probabilities numerically 0 or 1 occurred 
2: glm.fit: fitted probabilities numerically 0 or 1 occurred 
3: glm.fit: fitted probabilities numerically 0 or 1 occurred 
4: glm.fit: fitted probabilities numerically 0 or 1 occurred 
5: glm.fit: algorithm did not converge 
6: glm.fit: fitted probabilities numerically 0 or 1 occurred 
7: glm.fit: fitted probabilities numerically 0 or 1 occurred 
8: glm.fit: fitted probabilities numerically 0 or 1 occurred 
9: glm.fit: fitted probabilities numerically 0 or 1 occurred 

par(mfrow=c(1,1)) 
par(mar = c(5,5,14,5)) 
plot(subset(x, delta <2), labAsExpr = T, xlab=c("Predictor Variables for 'P. edwardsi' Dispersal"), ylab=c(expression(paste("Model Number by Cumulative Akaike Weight ", (omega))))) 

"Error in pal[, 1L + ((i - 1L)%%npal)] : incorrect number of dimensions"

有誰知道這是爲什麼發生？我對許多其他迭代使用了相同的代碼（即更改響應變量）並且沒有以前的問題。

Answer 1

這是STR（）調用的要發送到plot()物體在頂部的輸出：我懷疑自己只是做了一個限制性

> xsub <- subset(x, delta <2) 
> str(xsub) 
Classes ‘model.selection’ and 'data.frame': 1 obs. of 11 variables: 
$ (Intercept)   : num 17.6 
$ COLOUR_RF   : Factor w/ 1 level "+": NA 
$ FAMILY    : Factor w/ 1 level "+": NA 
$ FRUIT_TYPE   : Factor w/ 1 level "+": 1 
$ COLOUR_RF:FAMILY : Factor w/ 1 level "+": NA 
$ COLOUR_RF:FRUIT_TYPE: Factor w/ 1 level "+": NA 
$ df     : int 3 
$ logLik    : num -44.3 
$ AICc    : num 94.8 
$ delta    : num 0 
$ weight    : num 1 

這種調用並不能提供繪圖功能所需的儘可能多的信息來完成任何有用的工作。使用subset(x, delta <5)成功。

Answer 2

此問題是由於subset(x, delta < 2)僅選擇一種情況而引起的（請參閱x$delta）。顯然，函數plot.model.selection無法處理這個問題。你可以通過增加子集範圍來解決這個問題，或者通過在plot函數中插入一些代碼來解決這個錯誤。這是我的修正，加入行pal <- as.matrix(pal)：

plot0 = function (x, ylab = NULL, xlab = NULL, labels = attr(x, "terms"), 
       labAsExpr = FALSE, col = c("SlateGray", "SlateGray2"), col2 = "white", 
       border = par("col"), par.lab = NULL, par.vlab = NULL, axes = TRUE, 
       ann = TRUE, ...) 
{ 
    if (is.null(xlab)) 
    xlab <- NA 
    if (is.null(ylab)) 
    ylab <- expression("Cumulative Akaike weight" ~ ~(omega)) 
    op <- par(..., no.readonly = TRUE) 
    on.exit(par(op)) 
    cumweight <- cumsum(weight <- Weights(x)) 
    stdweight <- weight/max(weight) 
    n <- nrow(x) 
    m <- length(attr(x, "terms")) 
    plot.new() 
    plot.window(xlim = c(0, m), ylim = c(1, 0), xaxs = "i", 
       yaxs = "i") 
    pal <- if (is.na(col2)) 
    rbind(col) 
    else vapply(col, function(x) grDevices::rgb((grDevices::colorRamp(c(col2, 
                     x)))(stdweight), maxColorValue = 255), character(n)) 
    pal <- as.matrix(pal) # the only new line 
    npal <- ncol(pal) 

    for (i in 1L:m) rect(i - 1, c(0, cumweight), i, 
         c(cumweight, 1), 
         col = ifelse(is.na(x[, i]), NA, pal[, 1L + ((i - 1L)%%npal)]), 
         border = border) 
    if (ann) { 
    labCommonArg <- list(col = par("col.axis"), font = par("font.axis"), 
         cex = par("cex.axis")) 
    if (labAsExpr) { 
     labels <- gsub(":", "%*%", labels, perl = TRUE) 
     labels <- gsub("\\B_?(\\d+)(?![\\w\\._])", "[\\1]", 
        labels, perl = TRUE) 
     labels <- parse(text = labels) 
    } 
    arg <- c(list(side = 3L, padj = 0.5, line = 1, las = 2), 
      labCommonArg) 
    for (i in names(par.lab)) arg[i] <- par.lab[i] 
    if (is.expression(labels)) { 
     if (length(labels) != m) 
     stop("length of 'labels' is not equal to number of terms") 
     for (i in 1L:m) do.call("mtext", c(list(text = as.expression(labels[[i]]), 
               at = i - 0.5), arg)) 
    } 
    else if (!is.null(labels) && !is.na(labels)) { 
     if (length(labels) != m) 
     stop("length of 'labels' is not equal to number of terms") 
     do.call("mtext", c(list(text = labels, at = 1L:m - 
           0.5), arg)) 
    } 
    arg <- c(list(side = 4, las = 2, line = 1, adj = 1), 
      labCommonArg) 
    for (i in names(par.vlab)) arg[i] <- par.vlab[i] 
    ss <- weight > -(1.2 * strheight("I", cex = arg$cex)) 
    arg[["at"]] <- (c(0, cumweight[-n]) + cumweight)[ss]/2 
    arg[["text"]] <- rownames(x)[ss] 
    arg$line <- arg$line + max(strwidth(arg[["text"]], cex = arg$cex, 
             units = "in"))/par("mai")[4L] * par("mar")[4L] 
    do.call(mtext, arg) 
    title(ylab = ylab, xlab = xlab) 
    } 
    if (axes) { 
    axis(2L, col = border, col.ticks = border) 
    box(col = border) 
    } 
    invisible(x) 
} 

您還需要通過Weights = MuMIn:::Weights採取Weights功能出了隱藏的環境。那麼這個工作對我來說：

plot0(subset(x, delta < 2), labAsExpr = T, 
     xlab=c("Predictor Variables for 'P. edwardsi' Dispersal"), 
     ylab=c(expression(paste("Model Number by Cumulative Akaike Weight ", (omega)))))